This lecture covers dynamic programming concepts such as memoization and the bottom-up approach. It explains the process of optimizing recursive algorithms by storing results and solving smaller sub-problems first. The instructor demonstrates how to apply these techniques to problems like rod cutting and the change-making problem, providing insights into time complexity and optimal solution reconstruction.
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